similar to: Preparing for multi-core CPUs and parallel processing applications

I know this has been addressed before, but I'm still confused by the solution. When running TINN - R (ver 2.1.1.6) with R (2.8.0) I have lost the functionality of TINN-R It returns an error source(.trPaths[5], echo=TRUE, max.deparse.length=150) I modified the RProfile.site file as follows: options(pager="interal") .trPaths=c( 'C:/Documents and

Hello I have a Linux machine (Ubuntu 8.04 hardy, Gcc version 4.2.4 (i486-linux-gnu) currently running R 2.6.2. I'd like to upgrade to 2.10. First Question): What is the appropriate way to remove the old version of R? Part 2. After downloading r-base_2.10.0.orig.tar.gz and opening the archive. I ran the ./configure routine. It failed claiming that it could not find the F77 compiler. My

Hi, I need to create a plot (type = "h") and then overlay a skewed-normal curve on this distribution, but I'm not finding a procedure to accomplish this. I want to use the plot function here in order to control the bin distributions. I have explored the sn library and found the dsn function. dsn uses known location, scaling and shape parameters associated with a given input

I am using windows XP with R 2.8.1 I am generating a lattice plot of annual rain patterns using the following function: > xyplot(rain.stats$min+ rain.stats$max + rain.stats$ave ~ rain.stats$month |rain.stats$year, lty = 1, data = rain.stats, type = c("l","l", "l"), col = c("red", "blue", "green"), distribute.type =

Hello I've been asked to help evaluate a vegetation data set, specifically to examine it for community similarity. The initial problem I see is that the data is ordinal. At best this only captures a relative ranking of abundance and ordinal ranks are assigned after data collection. I've been trying to find a procedure in R that can handle ordinal based classification and so far have

Hello, I've been using ctree and have developed a 55 node - 28 terminal solution. As can be imagined, the plot is difficult to travel down each of the major branches. I've read the help files for ctree I saw where terminal nodes can be color coded. plot(airct, type = "simple") > plot(airct, terminal_panel = node_boxplot(airct, col = "blue", + fill = hsv(2/3,

Hello, I've been getting the following error when using the mlogit function from the mlogit package This is one of the examples provided in the Package "mlogit" January 27, 2010 description data("Fishing", package="mlogit") Fish <- mlogit.data(Fishing, varying = c(4:11), shape="wide", choice="mode") summary(mlogit(mode ~ pr + ca - 1,

Hello, I've tried to install randomForest on a Ubuntu 8.04 Hardy Heron system. I've repeatedly rec'd the error: > install.packages("randomForest", dependencies = TRUE) ERROR: compiliation failed for package 'randomForest' ** Removing '/home/admuser/R/i486-pc-linux-gnu-library/2.6/randomForest' The downloaded packages are in

I'd like to annotate an xyplot with an R^2 value, but can not find the syntax to define the superscript format for the text. I'd appreciate suggestions, xyplot(SharkSloughEggs.df$Sharkeggs.rel + SharkSloughEggs.df$SharkHatched.rel + SharkSloughEggs.df$SharkFlooded.rel + HSI.shark$MEAN ~ Year, pch=c(1,9,5,4), lty=c(1,6,3,4), lwd = c(2), col = c("black",

Hello, This is a re-submittal of question I submitted last week, but haven't rec'd any responses. I need to extract the probabilities used to construct the barplots displayed as part of the graph produced by plot("ctree"). For example, library(party) iris.ct <- ctree(Species ~ . , data = iris) plot(iris.ct) Instead of a simple example with only 4 terminal nodes, my

My data contains a variable "observation_date" and it contains values as: 1985-09-02 1985-09-15 1985-07-31 1985-09-02 I need to process data annually rather than daily, therefore I'm trying to 1) either extract the first 4 digits from this field and use them as a new variable "year" or 2) keep the variable as it is and process the analysis using the first 4 digits of

Thanks for the gracious assistance in advance I'm working on a non-metric scaling problem and am calculating the distance for input to isoMDS Here is the code library(MASS) vegdata <- tapply(Percent, list(PRIMARY_VE, MASTERID), sum) x.mat <- matrix(x, nrow=40, ncol=2750, byrow=TRUE, dimnames = c(dimnames(x)[1], dimnames(x)[2])) vegdata.dd <- dist(x) vegdata.dd <-

Hello everyone I'm working with R 2.8.1 on a windows machine I have a question regarding time series analysis The first question is how does R expect the input file to be structured? I'm working with a *.txt file similar to the abbreviated one here: Date,stage 4/2/1953,7.56 4/3/1953,7.56 4/4/1953,7.54 4/5/1953,7.53 4/6/1953,7.5 4/7/1953,7.47 4/8/1953,7.44 4/9/1953,7.41 4/10/1953,7.37

If someone can explain this odd behavior I'd appreciate it. I have a data.frame Cell.ave (attached and created via dput(Cell.ave, "Cell.ave") which contains three columns of parameters year, month and AveRain. I need to subset the data.frame by months such that DrySeaonMonths are 1,2,3,4, 11, and 12 or Jan - April, November and December and WetSeasonMonths are 5:10 or

Hello I'm working with a large hydrological data set stored in a netCDF format. The file stores x and y coordinates in the UTM projected coordinate system, yet when I use image to graphically display the z variable, the image is distorted in the sense that it does not plot the map in the correct spatial organization. I'm wondering if I need to define the projection of the netCDF file

Hi, The following script (which I did not develop) is used to calculate and plot a skewed normal curve. The script currently requires the user to input six parameters, rather than reading these directly from a file. I've been spinning wheels here, trying to figure out how to modify the script to automate it. I have four data sets, each in excess of 300 records that I need to process. My

Hello Trying to develop variograms and kriged surfaces from a point file. Here is what I've done so far. library(gstat) # also loads library(sp) library(lattice) soilpts$x <- soilpts$UTM_X soilpts$y <- soilpts$UTM_Y soil.dat <- subset(soilpts, select=c(x, y, Area, BulkDensity, LOI, TP, TN, TC, Total_Mg)) dim(soil.dat) [1] 1292 7 coordinates(soil.dat) <- ~ x+y

Hello, I am working with version 2.7.2 on a PC and have 2.8.0 available, but have not upgraded completely yet. I have 6 species for which I've run 6 unique environmental management scenarios against for comparison purposes. Each scenario is run for 36 years (1965 - 2000). Some of the species have subpopulations and other do not. For those with subpopulations (A, B, C, D, E, and F) I have

Hello. I'm working on a windows XP machine with R 2.8.1 I'm working with lattice and I don't understand how to set the size of the text for the labels. Can anyone suggest a solution? I'm establishing a melted dataframe first and then setting a key and calling the plot as follows; > key.variable <- list(space = "right", text = list(levels(wbirdm$variable)),

Hello I'm plotting a large suite of barcharts and need to modify the size of the text for both the yaxis and xaxis labels. I've tried using the following: > trellis.par.set(list(par.ylab.text = list(cex = 0.65)), trellis.par.set(list = par.xlab.text = list(cex = 0.65)))) On inspection, however after I invoke this line, > trellis.par.get("par.ylab.text") >